How Unprepared Are We For the Robot Revolution?

The revolution is here. It has already impacted how businesses operate and how we live. Neither the most alarming pessimists nor the most naively Panglossian optimists have a logical solution for addressing the dislocation that has ensued.

The problem is that society seems unwilling to accept any notion of collective responsibility for optimizing the transition. Without which we will then collectively endure the consequences. JL

Martin Ford reports in the Financial Times:

The most important immediate challenge we face will be adjusting to the economic and social implications of a robotic revolution in the workplace. That disruption is already beginning to unfold, and one might reasonably argue that its impact can already be measured in terms of the political upheaval occurring in both the US and Europe.
Google’s recent announcement that its DeepMind technology had defeated one of the world’s highest-ranked champions at the ancient game of Go is just one example of the many dramatic advances unfolding in the fields of artificial intelligence and robotics. Machines are rapidly taking on ever more challenging cognitive tasks, encroaching on the fundamental capability that sets humans apart as a species: our ability to make complex decisions, to solve problems — and, most importantly, to learn. DeepMind’s feat was especially remarkable not just because the technology ultimately prevailed, but because the system largely trained itself to do so. In the coming decades, machine learning is likely to be the primary driving force behind a Cambrian explosion of applications in robotics and software automation. It won’t be long before the tools and building blocks that enable engineers and entrepreneurs to create smart robotic systems will be so advanced and accessible that nearly any opportunity to leverage the technology will be identified and addressed almost immediately. The near-term future is likely to be transformed not by general purpose robots or AI systems but rather a nearly limitless number of specialised applications. Collectively, these systems are likely to span the entire job market and economy, ultimately consuming nearly any kind of work that is on some level routine and predictable. Sceptics will be quick to point out that history clearly shows that advancing technology creates new types of work even as it destroys existing occupations. This process will doubtless continue, but it seems unlikely that sufficient opportunities will be created to absorb the workers pushed out of traditional jobs. To take just one example, consider the impact of self-driving cars. Clearly, the jobs of millions of people who drive taxis or delivery vehicles or work for Uber will be at high risk. On the other hand, building a truly robotic car, capable of operating completely without human intervention, remains a substantial challenge. Autonomous car technology relies heavily on highly detailed advanced mapping of the routes to be driven. The problem is handling the unexpected and infrequent challenges that defy that kind of data-driven approach: the fallen tree that blocks the road, the unscheduled construction or any number of other unpredictable situations that might arise.
An obvious solution presents itself: keep people in the loop just to handle those unusual situations. It’s easy to imagine a future where vehicles operate 99 per cent autonomously, but somewhere a control centre contains specially trained people, ready to take over when a car signals that it has encountered something outside the bounds of its normal operating environment. Those controllers, of course, will be engaged in one of those “new” occupations on which we rest our hopes. But how many of those jobs will there be, relative to the number of driving jobs lost?

Needless to say, this mismatch between job destruction and creation isn’t going to be confined to driving. This basic approach — automating nearly all routine and predictable aspects of an occupation and then consolidating the remaining unpredictable tasks into a small number of jobs — is likely to be applied across the board. The low-wage service sector jobs in areas such as fast food and retail, which constitute a substantial fraction of the jobs being created by the economy in both the US and the UK, are certain to be heavily affected. Even more important will be all the white-collar occupations that involve relatively routine information analysis and manipulation. As these “good” jobs, often held by university graduates, begin to evaporate, faith in evermore education and training as the common solution to technological disruption of the job market seems likely to also erode.
All of this portends a social, economic and political disruption for which we are completely unprepared. Widespread unemployment (or even underemployment) has clear potential to rend the fabric of society. Beyond that, it also carries substantial economic risks: in a world with far too few jobs, who will have the income and confidence to purchase the products and services produced by the economy? Where will demand come from? For years, average households in the US have been relying ever more on debt to support their consumption. How will they continue to service those debts in a future where jobs are beginning to evaporate en masse?
In recent years, prominent individuals such as Stephen Hawking and Elon Musk have warned of the risks associated with “killer robots” or super-intelligent machines. While these concerns may some day be relevant, and while there are certainly important ethical considerations involving the use of autonomous systems in military and security applications, I would argue that the most important immediate challenge we face will be adjusting to the economic and social implications of a robotic revolution in the workplace. That disruption is already beginning to unfold, and one might reasonably argue that its impact can already be measured in terms of the political upheaval occurring in both the US and Europe. If we fail to have a meaningful public conversation about what robotics and artificial intelligence mean for the future, and develop workable ways in which to adapt our economy and society, then far greater, and more frightening, volatility is sure to soon arrive.